DBMS > Google BigQuery vs. OrientDB vs. STSdb vs. VelocityDB

System Properties Comparison Google BigQuery vs. OrientDB vs. STSdb vs. VelocityDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Multi-model DBMS (Document, Graph, Key/Value)

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store

Key-value store

Graph DBMS
Object oriented DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Score	0.05
Rank	#358	Overall
	#36	Graph DBMS
	#16	Object oriented DBMS

Website

cloud.google.com/bigquery

orientdb.org

github.com/STSSoft/STSdb4

velocitydb.com

Technical documentation

cloud.google.com/bigquery/docs

www.orientdb.com/docs/last/index.html

velocitydb.com/UserGuide

Developer

Google

OrientDB LTD; CallidusCloud; SAP

STS Soft SC

VelocityDB Inc

Initial release

2010

2011

Current release

3.2.29, March 2024

4.0.8, September 2015

7.x

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

GPLv2, commercial license available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

hosted

All OS with a Java JDK (>= JDK 6)

Windows

Any that supports .NET

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language, no joins

APIs and other access methods

RESTful HTTP/JSON API

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

.NET Client API

.Net

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C#
Java

.Net

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Java, Javascript

Triggers

Hooks

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Access rights for users and roles; record level security configurable

Based on Windows Authentication

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